lisa is not sure if m causes n, n causes m, or neither. in an attempt to come to a conclusion, she first…

lisa is not sure if m causes n, n causes m, or neither. in an attempt to come to a conclusion, she first plotted m on the x - axis, n on the y - axis, and used the linear regression feature of her graphing calculator. when she did this, she got a correlation coefficient (r) of 0.962 and a line with a slope of 2.3. she then plotted n on the x - axis, m on the y - axis, and used the linear regression feature of her graphing calculator. when she did this, she got a correlation coefficient (r) of 0.962 and a line with a slope of 0.4. which conclusion is the most valid? a m causes n. b n causes m. c m might cause n, or n might cause m. d m doesnt cause n, and n doesnt cause m.

lisa is not sure if m causes n, n causes m, or neither. in an attempt to come to a conclusion, she first plotted m on the x - axis, n on the y - axis, and used the linear regression feature of her graphing calculator. when she did this, she got a correlation coefficient (r) of 0.962 and a line with a slope of 2.3. she then plotted n on the x - axis, m on the y - axis, and used the linear regression feature of her graphing calculator. when she did this, she got a correlation coefficient (r) of 0.962 and a line with a slope of 0.4. which conclusion is the most valid? a m causes n. b n causes m. c m might cause n, or n might cause m. d m doesnt cause n, and n doesnt cause m.

Answer

Brief Explanations:

Correlation does not imply causation. Just because there is a high - correlation coefficient (0.962) in both plots of m and n in different axis - assignments, it doesn't mean one variable causes the other. There could be other factors or just a coincidental linear relationship.

Answer:

D. m doesn't cause n, and n doesn't cause m.